Commercial analysis
Market Intelligence and Competitor Analysis
Market-intelligence and competitor-analysis work across health technologies, including company search, horizon scanning, evidence comparison and adoption-readiness framing.
Quick scan
- Role
- Market-intelligence and competitor-analysis support for live innovation questions.
- Timeframe
- Placement period, 2024-2025
- Context
- Health Innovation East commercial innovation and market analysis work.
- Work mode
- Independently authored analyses and reusable research buildout.
- Outputs
- Structured company lists, competitor matrices, horizon scans and sector snapshots.
- Why it matters
- Shows I can turn noisy market evidence into reusable commercial judgement.
Context
Commercial health innovation depends on knowing the market quickly and carefully: who is active, what evidence they have, how mature the products are, where competitors sit in the pathway and what adoption questions remain open.
My role
I used CB Insights and secondary research to support market-intelligence work. I independently authored some internal market analyses and developed competitor-analysis materials across digital health, diagnostics, AI-enabled tools and MedTech.
Approach
The work turned large and often noisy sources into practical decision support for colleagues.
- Company searches and structured company lists.
- Technology categorisation, funding and maturity signals.
- Comparator products, public evidence signals and pathway relevance.
- Regulatory position where public and safe to discuss.
- Interoperability, integration and adoption-risk questions.
Selected outputs
- Reusable research views and horizon-scanning summaries.
- Sector snapshots and technology landscape summaries.
- Competitor matrices and stakeholder decision-driver summaries.
- Adoption-readiness framing for internal commercial analysis.
What this shows
I turned noisy market data into reusable decision support: structured company lists, competitor matrices, funding and maturity signals, evidence comparisons, and pathway-fit questions that colleagues could use quickly. The strongest proof here is not that I could research a market once, but that I helped build repeatable market-intelligence capability that made live innovation questions easier to answer.